QI HUANG, PHD, is a Professor with the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC) and Director, Key Lab of Power System Wide Area Measurement and Control, Sichuan Province, P.R. China. ARSALAN HABIB KHAWAJA, PHD, is an Assistant Professor with the U.S.-Pakistan Center for Advanced Studies in Energy (USPCASE), National University of Sciences and Technology (NUST), Pakistan. YAFENG CHEN is with the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), P.R. China. JIAN LI is Associate Professor at the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), P.R. China.

• Foreword xiPreface xvAcknowledgments xvii1 Introduction 11.1 Magnetism and Magnetic Fields: A Historical View 11.1.1 A Historical View of Magnetism 11.1.2 Magnetic Field 41.1.3 The Mathematics of Magnetism 51.1.4 Magnetism in Daily Life 71.1.5 Magnetic Fields in Industry 91.2 Magnetic Fields in Modern Power Systems 101.2.1 Components of Modern Power Systems 101.2.2 Magnetic Field Detection and Interpretation 151.3 Magnetics in Smart Grids 191.3.1 Magnetic Field in Lieu of Smart Grid Objectives 191.3.2 Magnetic Field Measurements for Innovative Applications 22Bibliography 222 State of the Art Magnetoresistance Based Magnetic Field Measurement Technologies 252.1 Introduction 252.2 Progress in MR Sensing Technologies 252.2.1 AMR Sensors 262.2.2 GMR Sensors 292.2.3 TMR Sensors 322.2.4 CMR Sensors 342.3 Limitations of MR Effect Based Sensors 352.3.1 Noise Performance 362.3.2 Noise Shielding and PreventiveMeasures 392.3.3 Cross-axis Noise 412.4 Sensor Circuitry Design and Signal Processing 422.4.1 AMR: Set/reset Pulse 432.4.2 GMR: Temperature Compensation and Unipolar Output 462.4.3 TMR: Higher Noise Level at Low Frequencies 482.5 Overview of Established Magnetic Field Sensing Technologies 49Bibliography 503 Magnetic Field Measurement for Power Transmission Systems 533.1 Introduction 533.2 Electric Current Reconstruction 553.2.1 Reconstruction with Stochastic Optimization Techniques 553.2.2 Reconstruction with Optimal Placement of Minimum Sensing Nodes 613.3 Monitoring of Operation Parameters of Power Transmission Lines 793.3.1 Conductor Elongation and Motion 793.3.2 Detection and Estimation 823.4 Spatial Monitoring of HVTLs in Real-world Scenarios 893.4.1 Mathematic Model of HVTLs in Real-world Scenarios 893.4.2 MF of HVTLs in Motion for Real-world Scenarios 953.4.3 MF of Conductors for Random Bi-directional Motion 973.4.4 A Unified Algorithm for Sag and Conductor Motion Detection 1003.4.5 Validation of the Proposed Approach 1023.4.6 Noise Tolerance and Uncertainty Analysis 1063.5 Unified Current Reconstruction and Operation Parameters of HVTLs 1093.6 Fault Location in Overhead HVTLs 1193.6.1 Types of Short-circuit Faults 1193.6.2 Fault Detection with Magnetic Sensors 121Bibliography 1404 Magnetic Field Measurement for Modern Substations 1434.1 Introduction to GIS-based Substations 1434.1.1 Smart Substations 1434.1.2 Gas-insulated Switchgear 1444.1.3 GIS-based Substations 1454.2 MR-based Electronic Current Transformers 1464.2.1 Experimental Research on Hysteresis Effects in MR Sensors 1474.2.2 MR Sensors with Magnetic Shielding 1594.3 Broadband Magnetic Field Characterization 1704.3.1 Transient Magnetic Field Events 1704.3.2 Evaluation of TMF Event Impact on Electronic Equipment 1714.4 Broadband Point Measurement of the TMF in Substations with MR Sensors 1734.4.1 Effect of sensor size 1734.4.2 Design of a Point Measurement System 1754.4.3 Laboratory Testing of the Measurement System 1764.4.4 Onsite Testing 1794.5 Noise and External Field Protection 1804.5.1 MR Sensor Array Based Interference-rejecting Current Measurement Method 1834.5.2 Adaptive Filter Algorithm Based Current Measurement 1944.5.3 Current Measurement Under Strong Interference 202Bibliography 2145 Magnetic Field Measurement for Power Distribution Systems 2195.1 Introduction 2195.2 Magnetic Field Measurement Based Non-invasive Detection 2205.3 Magnetic Sensors for HEMSs 2235.3.1 Magnetic Sensors Enable Non-intrusive Monitoring for HEMSs 2245.3.2 Detection Method for Edge Identification 2265.3.3 Discussion 2415.4 Magnetic Field Measurement Based Fault Location and Identification 2425.4.1 Introduction 2425.4.2 MR Based Non-invasive Identification Technique 2435.4.3 Distributed Sensor Network Based Fault Location and Identification 2455.5 Magnetic Sensors for Survey of EMF Exposure 2475.5.1 Magnetic Fields and Health 2475.5.2 Magnetic Environment Monitoring Systems 2495.5.3 Selection of Sensors 2515.5.4 System Design 2525.6 Collection of Energy Big Data 2555.6.1 Concept of Big Data 2555.6.2 Energy Big Data 2575.6.3 Non-invasive Collection of Energy Big Data 259Bibliography 2606 Innovative Magnetic Field Measurement for Power Generation Systems 2656.1 Introduction 2656.2 Condition Monitoring of Synchronous Machines 2666.2.1 Introduction 2666.2.2 Speed Monitoring 2676.2.3 Vibration Monitoring 2686.2.4 Crack Detection 2706.2.5 Electrical Machine Signature Identification 2706.2.6 Magnetic Field Measurement for Condition Monitoring of Synchronous Generators 2716.3 Magnetic Field and Renewable Energy 2726.3.1 Commonly Used Renewable Energy Sources 2736.3.2 Potential Applications 2746.3.3 Challenges 279Bibliography 2807 Future Vision 2857.1 Magnetic Field Based Instrumentation and Measurement in Smart Grids 2857.1.1 Transmission Systems 2857.1.2 Distribution Systems 2867.1.3 Generation Systems 2877.2 Integration with Existing Power Systems 2887.2.1 Chances 2897.2.2 Challenges 2907.3 Future Development 2917.3.1 Performances 2927.3.2 Standardization 2927.3.3 Applications 293Bibliography 294Index 295

QI HUANG, PHD, is a Professor with the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC) and Director, Key Lab of Power System Wide Area Measurement and Control, Sichuan Province, P.R. China. ARSALAN HABIB KHAWAJA, PHD, is an Assistant Professor with the U.S.-Pakistan Center for Advanced Studies in Energy (USPCASE), National University of Sciences and Technology (NUST), Pakistan. YAFENG CHEN is with the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), P.R. China. JIAN LI is Associate Professor at the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), P.R. China.

• Foreword xiPreface xvAcknowledgments xvii1 Introduction 11.1 Magnetism and Magnetic Fields: A Historical View 11.1.1 A Historical View of Magnetism 11.1.2 Magnetic Field 41.1.3 The Mathematics of Magnetism 51.1.4 Magnetism in Daily Life 71.1.5 Magnetic Fields in Industry 91.2 Magnetic Fields in Modern Power Systems 101.2.1 Components of Modern Power Systems 101.2.2 Magnetic Field Detection and Interpretation 151.3 Magnetics in Smart Grids 191.3.1 Magnetic Field in Lieu of Smart Grid Objectives 191.3.2 Magnetic Field Measurements for Innovative Applications 22Bibliography 222 State of the Art Magnetoresistance Based Magnetic Field Measurement Technologies 252.1 Introduction 252.2 Progress in MR Sensing Technologies 252.2.1 AMR Sensors 262.2.2 GMR Sensors 292.2.3 TMR Sensors 322.2.4 CMR Sensors 342.3 Limitations of MR Effect Based Sensors 352.3.1 Noise Performance 362.3.2 Noise Shielding and PreventiveMeasures 392.3.3 Cross-axis Noise 412.4 Sensor Circuitry Design and Signal Processing 422.4.1 AMR: Set/reset Pulse 432.4.2 GMR: Temperature Compensation and Unipolar Output 462.4.3 TMR: Higher Noise Level at Low Frequencies 482.5 Overview of Established Magnetic Field Sensing Technologies 49Bibliography 503 Magnetic Field Measurement for Power Transmission Systems 533.1 Introduction 533.2 Electric Current Reconstruction 553.2.1 Reconstruction with Stochastic Optimization Techniques 553.2.2 Reconstruction with Optimal Placement of Minimum Sensing Nodes 613.3 Monitoring of Operation Parameters of Power Transmission Lines 793.3.1 Conductor Elongation and Motion 793.3.2 Detection and Estimation 823.4 Spatial Monitoring of HVTLs in Real-world Scenarios 893.4.1 Mathematic Model of HVTLs in Real-world Scenarios 893.4.2 MF of HVTLs in Motion for Real-world Scenarios 953.4.3 MF of Conductors for Random Bi-directional Motion 973.4.4 A Unified Algorithm for Sag and Conductor Motion Detection 1003.4.5 Validation of the Proposed Approach 1023.4.6 Noise Tolerance and Uncertainty Analysis 1063.5 Unified Current Reconstruction and Operation Parameters of HVTLs 1093.6 Fault Location in Overhead HVTLs 1193.6.1 Types of Short-circuit Faults 1193.6.2 Fault Detection with Magnetic Sensors 121Bibliography 1404 Magnetic Field Measurement for Modern Substations 1434.1 Introduction to GIS-based Substations 1434.1.1 Smart Substations 1434.1.2 Gas-insulated Switchgear 1444.1.3 GIS-based Substations 1454.2 MR-based Electronic Current Transformers 1464.2.1 Experimental Research on Hysteresis Effects in MR Sensors 1474.2.2 MR Sensors with Magnetic Shielding 1594.3 Broadband Magnetic Field Characterization 1704.3.1 Transient Magnetic Field Events 1704.3.2 Evaluation of TMF Event Impact on Electronic Equipment 1714.4 Broadband Point Measurement of the TMF in Substations with MR Sensors 1734.4.1 Effect of sensor size 1734.4.2 Design of a Point Measurement System 1754.4.3 Laboratory Testing of the Measurement System 1764.4.4 Onsite Testing 1794.5 Noise and External Field Protection 1804.5.1 MR Sensor Array Based Interference-rejecting Current Measurement Method 1834.5.2 Adaptive Filter Algorithm Based Current Measurement 1944.5.3 Current Measurement Under Strong Interference 202Bibliography 2145 Magnetic Field Measurement for Power Distribution Systems 2195.1 Introduction 2195.2 Magnetic Field Measurement Based Non-invasive Detection 2205.3 Magnetic Sensors for HEMSs 2235.3.1 Magnetic Sensors Enable Non-intrusive Monitoring for HEMSs 2245.3.2 Detection Method for Edge Identification 2265.3.3 Discussion 2415.4 Magnetic Field Measurement Based Fault Location and Identification 2425.4.1 Introduction 2425.4.2 MR Based Non-invasive Identification Technique 2435.4.3 Distributed Sensor Network Based Fault Location and Identification 2455.5 Magnetic Sensors for Survey of EMF Exposure 2475.5.1 Magnetic Fields and Health 2475.5.2 Magnetic Environment Monitoring Systems 2495.5.3 Selection of Sensors 2515.5.4 System Design 2525.6 Collection of Energy Big Data 2555.6.1 Concept of Big Data 2555.6.2 Energy Big Data 2575.6.3 Non-invasive Collection of Energy Big Data 259Bibliography 2606 Innovative Magnetic Field Measurement for Power Generation Systems 2656.1 Introduction 2656.2 Condition Monitoring of Synchronous Machines 2666.2.1 Introduction 2666.2.2 Speed Monitoring 2676.2.3 Vibration Monitoring 2686.2.4 Crack Detection 2706.2.5 Electrical Machine Signature Identification 2706.2.6 Magnetic Field Measurement for Condition Monitoring of Synchronous Generators 2716.3 Magnetic Field and Renewable Energy 2726.3.1 Commonly Used Renewable Energy Sources 2736.3.2 Potential Applications 2746.3.3 Challenges 279Bibliography 2807 Future Vision 2857.1 Magnetic Field Based Instrumentation and Measurement in Smart Grids 2857.1.1 Transmission Systems 2857.1.2 Distribution Systems 2867.1.3 Generation Systems 2877.2 Integration with Existing Power Systems 2887.2.1 Chances 2897.2.2 Challenges 2907.3 Future Development 2917.3.1 Performances 2927.3.2 Standardization 2927.3.3 Applications 293Bibliography 294Index 295

QI HUANG, PHD, is a Professor with the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC) and Director, Key Lab of Power System Wide Area Measurement and Control, Sichuan Province, P.R. China. ARSALAN HABIB KHAWAJA, PHD, is an Assistant Professor with the U.S.-Pakistan Center for Advanced Studies in Energy (USPCASE), National University of Sciences and Technology (NUST), Pakistan. YAFENG CHEN is with the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), P.R. China. JIAN LI is Associate Professor at the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), P.R. China.

• Foreword xiPreface xvAcknowledgments xvii1 Introduction 11.1 Magnetism and Magnetic Fields: A Historical View 11.1.1 A Historical View of Magnetism 11.1.2 Magnetic Field 41.1.3 The Mathematics of Magnetism 51.1.4 Magnetism in Daily Life 71.1.5 Magnetic Fields in Industry 91.2 Magnetic Fields in Modern Power Systems 101.2.1 Components of Modern Power Systems 101.2.2 Magnetic Field Detection and Interpretation 151.3 Magnetics in Smart Grids 191.3.1 Magnetic Field in Lieu of Smart Grid Objectives 191.3.2 Magnetic Field Measurements for Innovative Applications 22Bibliography 222 State of the Art Magnetoresistance Based Magnetic Field Measurement Technologies 252.1 Introduction 252.2 Progress in MR Sensing Technologies 252.2.1 AMR Sensors 262.2.2 GMR Sensors 292.2.3 TMR Sensors 322.2.4 CMR Sensors 342.3 Limitations of MR Effect Based Sensors 352.3.1 Noise Performance 362.3.2 Noise Shielding and PreventiveMeasures 392.3.3 Cross-axis Noise 412.4 Sensor Circuitry Design and Signal Processing 422.4.1 AMR: Set/reset Pulse 432.4.2 GMR: Temperature Compensation and Unipolar Output 462.4.3 TMR: Higher Noise Level at Low Frequencies 482.5 Overview of Established Magnetic Field Sensing Technologies 49Bibliography 503 Magnetic Field Measurement for Power Transmission Systems 533.1 Introduction 533.2 Electric Current Reconstruction 553.2.1 Reconstruction with Stochastic Optimization Techniques 553.2.2 Reconstruction with Optimal Placement of Minimum Sensing Nodes 613.3 Monitoring of Operation Parameters of Power Transmission Lines 793.3.1 Conductor Elongation and Motion 793.3.2 Detection and Estimation 823.4 Spatial Monitoring of HVTLs in Real-world Scenarios 893.4.1 Mathematic Model of HVTLs in Real-world Scenarios 893.4.2 MF of HVTLs in Motion for Real-world Scenarios 953.4.3 MF of Conductors for Random Bi-directional Motion 973.4.4 A Unified Algorithm for Sag and Conductor Motion Detection 1003.4.5 Validation of the Proposed Approach 1023.4.6 Noise Tolerance and Uncertainty Analysis 1063.5 Unified Current Reconstruction and Operation Parameters of HVTLs 1093.6 Fault Location in Overhead HVTLs 1193.6.1 Types of Short-circuit Faults 1193.6.2 Fault Detection with Magnetic Sensors 121Bibliography 1404 Magnetic Field Measurement for Modern Substations 1434.1 Introduction to GIS-based Substations 1434.1.1 Smart Substations 1434.1.2 Gas-insulated Switchgear 1444.1.3 GIS-based Substations 1454.2 MR-based Electronic Current Transformers 1464.2.1 Experimental Research on Hysteresis Effects in MR Sensors 1474.2.2 MR Sensors with Magnetic Shielding 1594.3 Broadband Magnetic Field Characterization 1704.3.1 Transient Magnetic Field Events 1704.3.2 Evaluation of TMF Event Impact on Electronic Equipment 1714.4 Broadband Point Measurement of the TMF in Substations with MR Sensors 1734.4.1 Effect of sensor size 1734.4.2 Design of a Point Measurement System 1754.4.3 Laboratory Testing of the Measurement System 1764.4.4 Onsite Testing 1794.5 Noise and External Field Protection 1804.5.1 MR Sensor Array Based Interference-rejecting Current Measurement Method 1834.5.2 Adaptive Filter Algorithm Based Current Measurement 1944.5.3 Current Measurement Under Strong Interference 202Bibliography 2145 Magnetic Field Measurement for Power Distribution Systems 2195.1 Introduction 2195.2 Magnetic Field Measurement Based Non-invasive Detection 2205.3 Magnetic Sensors for HEMSs 2235.3.1 Magnetic Sensors Enable Non-intrusive Monitoring for HEMSs 2245.3.2 Detection Method for Edge Identification 2265.3.3 Discussion 2415.4 Magnetic Field Measurement Based Fault Location and Identification 2425.4.1 Introduction 2425.4.2 MR Based Non-invasive Identification Technique 2435.4.3 Distributed Sensor Network Based Fault Location and Identification 2455.5 Magnetic Sensors for Survey of EMF Exposure 2475.5.1 Magnetic Fields and Health 2475.5.2 Magnetic Environment Monitoring Systems 2495.5.3 Selection of Sensors 2515.5.4 System Design 2525.6 Collection of Energy Big Data 2555.6.1 Concept of Big Data 2555.6.2 Energy Big Data 2575.6.3 Non-invasive Collection of Energy Big Data 259Bibliography 2606 Innovative Magnetic Field Measurement for Power Generation Systems 2656.1 Introduction 2656.2 Condition Monitoring of Synchronous Machines 2666.2.1 Introduction 2666.2.2 Speed Monitoring 2676.2.3 Vibration Monitoring 2686.2.4 Crack Detection 2706.2.5 Electrical Machine Signature Identification 2706.2.6 Magnetic Field Measurement for Condition Monitoring of Synchronous Generators 2716.3 Magnetic Field and Renewable Energy 2726.3.1 Commonly Used Renewable Energy Sources 2736.3.2 Potential Applications 2746.3.3 Challenges 279Bibliography 2807 Future Vision 2857.1 Magnetic Field Based Instrumentation and Measurement in Smart Grids 2857.1.1 Transmission Systems 2857.1.2 Distribution Systems 2867.1.3 Generation Systems 2877.2 Integration with Existing Power Systems 2887.2.1 Chances 2897.2.2 Challenges 2907.3 Future Development 2917.3.1 Performances 2927.3.2 Standardization 2927.3.3 Applications 293Bibliography 294Index 295